Triple

T2900980
Position Surface form Disambiguated ID Type / Status
Subject Greyhound E62651 entity
Predicate starring P1507 FINISHED
Object Elisabeth Shue E254706 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Elisabeth Shue | Statement: [Greyhound, starring, Elisabeth Shue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elisabeth Shue
Context triple: [Greyhound, starring, Elisabeth Shue]
  • A. Elisabeth Shue chosen
    Elisabeth Shue is an American actress known for her roles in films such as "The Karate Kid," "Adventures in Babysitting," and "Leaving Las Vegas," for which she received an Academy Award nomination.
  • B. Anne McDonnell
    Anne McDonnell was an American socialite best known as the first wife of industrialist Henry Ford II.
  • C. Nancy Walker
    Nancy Walker was an American actress and comedian best known for her sharp-tongued character roles in film, television, and Broadway musicals.
  • D. Jill Clayburgh
    Jill Clayburgh was an American actress acclaimed for her intelligent, nuanced performances in 1970s and 1980s films, including multiple Academy Award–nominated roles.
  • E. Tyne Daly
    Tyne Daly is an American actress acclaimed for her powerful performances in television dramas, film, and theater, including her iconic role in the series "Cagney & Lacey."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0b261c081909b66b21520b4731b completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b224a78bbc8190b4f4cdb058d5a176 completed March 12, 2026, 2:27 a.m.
Created at: March 6, 2026, 10:10 p.m.